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Canopy Cover As the Key Factor for Occurrence and Species Richness Of Aquatic Botany 137 (2017) 24–29 Contents lists available at ScienceDirect Aquatic Botany jou rnal homepage: www.elsevier.com/locate/aquabot Canopy cover as the key factor for occurrence and species richness of subtropical stream green algae (Chlorophyta) a,∗ b a Cleto Kaveski Peres , Aurélio Fajar Tonetto , Michel Varajão Garey , b Ciro Cesar Zanini Branco a Federal University of Latin American Integration (UNILA), Latin American Institute of Life and Nature Sciences, Foz do Iguac¸ u, Paraná, Brazil b São Paulo State University (UNESP), Laboratory of Aquatic Biology, Assis, São Paulo, Brazil a r t i c l e i n f o a b s t r a c t Article history: Understanding how local and regional environmental factors influence species richness remains a key Received 1 March 2016 issue in ecology. Green algae (Chlorophyta) are a diverse and widely occurring group, which may be a Received in revised form 1 November 2016 good model for studying the factors that influence species richness at local and regional scales. Here, we Accepted 8 November 2016 tested the influence of local (water quality and structural complexity) and regional environmental factors Available online 9 November 2016 (phyto-ecological regions) on the occurrence and species richness of macroscopic green algae (MGA) in subtropical streams. We sampled algae in 105 streams located in the four major phyto-ecological Keywords: regions of the Brazilian subtropics. We used cross-transect technique in streams to sample algae and Benthic macroalgae environmental variables. To determine the most important variables in species occurrence and richness, Brazilian streams Shading we used Hierarchical Partitioning analysis (HP). We found that canopy cover alone explained 34% of MGA Phyto-ecological region occurrence, regardless of phyto-ecological region. At the sites where MGA occurred, the species richness was determined by both regional and local factors. The species richness was mainly influenced by phyto- ecological region, which explained 34% of the variation in species richness, along with canopy cover and pH which explaining 22% and 15% respectively. The highest richness was found in non-forested regions, in transects without canopy cover, and slightly acidic pH. Our results illustrate how the combination of regional and local factors can shape the spatial distribution of species richness and are pivotal to understanding richness patterns at broad spatial scales. © 2016 Elsevier B.V. All rights reserved. 1. Introduction Environmental gradients have been widely related to photo- synthetic organisms in lotic habitats. For instance, nutrient (e.g., Hypotheses to explain species distribution in space usually conductivity, nitrogen, phosphorus), light availability (e.g., canopy involve local and regional scales (Shurin et al., 2000). The regional cover, turbidity), temperature, pH, hydraulic conditions (e.g., water species pool is determined by biogeographic and evolutionary velocity and depth), grazing rate, and stable substrate availability processes, such as speciation, extinction and migration (Ricklefs, (Allan and Castillo, 2007) are the most important factors deter- 2004; Harrison and Cornell, 2008). Furthermore, these processes mining photosynthetic organisms distribution in stream realms. are influenced by geomorphological and environmental character- These factors exhibit a wide spatial variation, so their influence is istics (Rahbek and Graves, 2001) and historical variations in climate related to spatial scale, ranging from microhabitat to regional scale of each region (Carnaval et al., 2009). Thus, species richness may (Frissell et al., 1986), what reflects in ecological patterns still not vary between regions as a result of these factors. At the local scale, completely understood or fairly predictable. Hence, more effort is species composition is a result of species sorting from the regional needed to uncover some neglected points regarding ecological dis- species pool (Ricklefs, 2004; Vellend, 2010) influenced mainly by tribution of stream dwellers. For example, determining how local local environmental characteristics (Tuomisto et al., 2014) and and regional environmental factors influence species richness is a biotic factors (Morin, 1999), with species tracking environmental key issue in ecology (Ricklefs, 2004, 2008; Brooker et al., 2009), but variations. this approach remains seldom applied for stream algae. Green algae (division Chlorophyta) are important primary pro- ducers in streams (Stevenson, 1996), commonly having higher ∗ richness than other macroalgal groups. Thus, macroscopic green Corresponding author. algae (MGA) are an interesting group of organisms to investigate E-mail addresses: [email protected], [email protected] (C.K. Peres). http://dx.doi.org/10.1016/j.aquabot.2016.11.004 0304-3770/© 2016 Elsevier B.V. All rights reserved. C.K. Peres et al. / Aquatic Botany 137 (2017) 24–29 25 factors related to richness variations at both local and regional scales. For example, a recent study (Branco et al., 2014) showed that the influence of spatial (e.g. related to dispersal process) and environmental processes (e.g. niche-based process) on the species composition of stream macroalgae varies among taxonomic groups (Cyanobacteria, Chlorophyta, and Rhodophyta). For instance, the taxonomic composition of green algae is influenced by both envi- ronment and space, while cyanobacteria only by environment and Rhodophyta only by space (Branco et al., 2014). Thus, local and regional factors may influence algal groups differently. Specifically for MGA, most studies have been conducted at small spatial scales or with limited number of species (Biggs and Price, 1987; Dodds and Gudder, 1992; Okada and Watanabe, 2002). Most of the eco- logical information about MGA comes from studies dealing with all groups of stream macroalgae. In these studies, some patterns are usually common, such as low endemism rate in each region (Borges and Necchi, 2006), occurrence in a few streams in a region Fig. 1. Percentage of stream transects sampled in each canopy cover class (total bars) (Branco et al., 2009), dominance by a few species (Necchi et al., and percentage of streams with green algae species occurrence in each canopy cover 2000; Borges and Necchi, 2006), and local distribution in a mosaic class (black bars). (Necchi et al., 2000, 2003). Nevertheless, how environmental vari- ables determine these distribution patterns is still poorly known (Branco et al., 2009). 2. Material and methods The major capability of green algae to grow in habitats with higher irradiance is well accepted and recognized among special- 2.1. Study region ists (Hill, 1996; and references therein). Indeed, previous studies showed that unshaded environments support higher primary pro- The sampled area comprises the Brazilian subtropical region duction and abundance of green algae. However, the role of ◦ ◦ ◦ ◦ (33 44 59” S; 48 01 08” W and 22 31 10” S; 57 36 05” W; Branco irradiance as a key factor on MGA occurrence and species richness is et al., 2014; see their Fig. 1), and is included in the states of Paraná, not clear at either regional or local scale. For example, open stream Santa Catarina and Rio Grande do Sul, located in southern Brazil. segments do not ensure the presence or high species richness of The region belongs to humid subtropical zone of oceanic climate, MGA (Branco and Necchi, 1996; Necchi et al., 2000) and the land- without a defined dry season (Alvares et al., 2013). The Brazilian scape could be exhibiting an important contribution (Oliveira et al., subtropical area is dominated basically by four phyto-ecological 2013). Hence, we expect that equally opened stream segments, but regions (IBGE, 1992) arranged in a mosaic: Seasonal Forest (SF); from distinct phyto-ecological regions, can exhibit different species Mixed Ombrophilous Forest (MOF); Dense Ombrophilous Forest richness. This logic led us to assess the species richness and occur- (DOF), and Steppe (ST). These formations were formed and shaped rence of MGA regarding environmental factors at local and regional by fire during the quaternary climate changes (Behling and Pillar, scales in order to check how environmental variables are determin- 2007). Climatic conditions determine these four phyto-ecological ing the distribution pattern of MGA. regions (IBGE, 1992). DOF has stable climate defined by high and Herein, we tested the influence of local (water quality regular rainfall throughout the year, while in SF, MOF and ST the and stream structural complexity) and regional factors (phyto- precipitation is sparsely distributed along the year. Regarding tem- ecological regions) on the occurrence and species richness of MGA perature, ST exhibit the highest annual amplitude (winter with in subtropical streams. We first assessed the occurrence (presence frost) and DOF exhibit the lowest temperature variation, while in stream segment) of MGA among all studied streams, regardless SF and MOF exhibit an intermediate variation. MOF cover higher of species identity, abundance or species number. After that, we altitude areas (more than 700 m a.s.l.) than SF. analyzed which factors are determining the MGA species richness We sampled 105 streams in 10 protected areas distributed in in the streams. For this, we sampled MGA in four phyto-ecological four vegetation formations of southern Brazil (Table 1). The region regions that encompass very different climatic conditions and veg- and stream segments are the same used by Branco et al. (2014) see etation
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